Methods and systems for generating alerts or recommend incentives for a loyalty program that provides incentives to cardholders in connection with transactions between the cardholders and merchants are disclosed. A merchant is identified. Transaction data reflective of completed transactions are received by way of a network. The transaction data is processed to generate an alert notifying the identified merchant of an event or trend, or to generate a recommended incentive that defines a benefit to be provided by the identified merchant to a cardholder upon the occurrence of an anticipated transaction.
Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: receiving transaction data reflective of each of a plurality of completed transactions; and for each said transaction: processing the received transaction data to identify at least one accountholder attribute; identifying a merchant; identifying at least one accountholder; identifying an anticipated transaction between the merchant and the at least one accountholder; generating, using a neural network of an artificial intelligence engine, a recommended incentive for the identified at least one accountholder based on the at least one accountholder attribute, wherein: the recommended incentive defines a benefit to be provided by the identified merchant to the identified at least one accountholder upon the occurrence of the anticipated transaction; and the benefit is that the merchant of the anticipated transaction has agreed to make a donation to an entity designated by the identified at least one accountholder upon the occurrence of the anticipated transaction at: a predetermined time of day; and a predetermined geographic location; and for the identified at least one accountholder, electronically transmitting to a logical address corresponding to the identified at least one accountholder an alert of the benefit.
This invention relates to a system and method for generating and delivering personalized incentives in e-commerce and retail environments. The problem addressed is how to effectively encourage anticipated transactions between merchants and accountholders by offering relevant and appealing benefits. The method involves receiving data from completed transactions. For each transaction, this data is processed to extract attributes of the accountholder. A merchant and at least one accountholder are identified, along with an anticipated future transaction between them. An artificial intelligence engine, specifically a neural network, is then used to generate a recommended incentive for the accountholder. This incentive is a benefit that the merchant agrees to provide to the accountholder if the anticipated transaction occurs. The benefit is structured as a donation by the merchant to an entity chosen by the accountholder, and this donation is triggered by the anticipated transaction happening at a specific time of day and in a particular geographic location. Finally, an alert detailing this benefit is electronically transmitted to the accountholder at their designated logical address.
2. The method as defined in claim 1 , wherein the anticipated transaction is identified based on the identified at least one accountholder attribute.
A system and method for identifying and processing anticipated transactions in a financial account management system. The technology addresses the problem of efficiently detecting and handling upcoming transactions to improve financial planning, fraud detection, and customer service. The method involves analyzing account holder attributes such as transaction history, spending patterns, and demographic information to predict future transactions. These attributes are used to identify specific anticipated transactions, allowing the system to preemptively process or flag them for further action. The system may also adjust transaction limits, notify the account holder, or apply fraud detection protocols based on the identified transaction. By leveraging account holder attributes, the method enhances accuracy in transaction prediction and reduces false positives in fraud detection. The approach improves financial management by providing timely insights and automated responses to anticipated financial activities.
3. The method as defined in claim 2 , wherein the at least one accountholder attribute is based on criteria selected from the group consisting of: a “Bank Identification Number” (BIN) range; demographics of the accountholder; the transaction and the merchant; and preferences of the identified at least one accountholder, wherein the at least one accountholder is identified based on the preferences.
This invention relates to a system for processing financial transactions, specifically focusing on dynamically selecting transaction processing rules based on accountholder attributes. The problem addressed is the need for flexible and personalized transaction handling in financial systems, where static rules may not adequately account for variations in accountholder behavior, preferences, or risk profiles. The method involves identifying at least one accountholder attribute to determine how a transaction should be processed. These attributes are selected from a predefined set of criteria, including the Bank Identification Number (BIN) range associated with the accountholder’s account, demographic information about the accountholder, details about the transaction itself and the merchant involved, and the accountholder’s preferences. The accountholder is identified based on their preferences, which may include transaction limits, preferred payment methods, or other customizable settings. The system then applies the appropriate processing rules based on the identified attributes, ensuring transactions are handled in a manner that aligns with the accountholder’s profile and preferences. This approach enhances security, personalization, and efficiency in transaction processing by dynamically adapting to individual accountholder needs.
4. The method as defined in claim 2 , wherein: the at least one accountholder attribute is based on a transaction history of the identified at least one accountholder; and the transaction history identifies purchases of goods and services, and merchants the goods and services were purchased from.
This invention relates to financial transaction analysis, specifically using accountholder attributes derived from transaction history to enhance financial services. The problem addressed is the need for more personalized and context-aware financial decision-making, such as fraud detection, credit scoring, or targeted offers, by leveraging detailed transaction patterns. The method involves analyzing transaction history to extract accountholder attributes, which include purchase behavior, merchant preferences, and spending habits. Transaction history is defined as records of purchases made by the accountholder, including the goods and services acquired and the merchants involved. These attributes are then used to generate insights or actions, such as identifying fraudulent transactions, adjusting credit limits, or recommending personalized financial products. The system processes transaction data to identify patterns, such as frequent purchases from specific merchants, recurring transactions, or unusual spending behavior. These patterns are used to refine financial models, improve risk assessment, or tailor services to individual accountholders. The approach ensures that financial decisions are based on real-world transactional evidence rather than static or limited data points.
5. The method as defined in claim 1 , wherein the instructions are further executable at the at least one processor to cause the system to generate an alert to notify the identified merchant of an identified event or trend.
This invention relates to a system for monitoring and analyzing merchant transactions to detect events or trends that may require attention. The system processes transaction data from multiple merchants to identify patterns, anomalies, or other significant occurrences that could impact business operations. When such an event or trend is detected, the system generates an alert to notify the relevant merchant, enabling timely action. The system includes at least one processor configured to execute instructions for analyzing transaction data. The analysis may involve comparing current transaction patterns against historical data, predefined thresholds, or industry benchmarks to detect deviations or trends. The system may also apply machine learning or statistical models to predict potential issues or opportunities. Once an event or trend is identified, the system generates an alert, which can be sent via email, SMS, or another notification method to the merchant. The alert may include details about the detected event, such as its nature, severity, and potential impact, allowing the merchant to respond appropriately. This approach helps merchants proactively manage their operations by providing real-time insights into transaction behavior, reducing risks, and improving decision-making. The system can be applied to various industries, including retail, e-commerce, and financial services, where transaction monitoring is critical.
6. The method as defined in claim 5 , wherein the identified event is selected from the group consisting of: a particular time of day; and a particular day of week.
This invention relates to event-based systems for triggering actions or processes, particularly in computing or automation environments. The problem addressed is the need for flexible and precise event detection to initiate specific operations at predefined times or intervals. The invention provides a method for identifying and responding to events, where the events are specifically defined as either a particular time of day or a particular day of the week. The system monitors for these events and executes a corresponding action when the event occurs. This allows for automated scheduling and task execution based on temporal conditions, such as running a backup at a specific time or activating a system at the start of a workday. The method ensures that actions are triggered reliably and predictably, improving efficiency in automated workflows. The invention may be applied in various domains, including software systems, industrial automation, and smart devices, where time-based or day-based triggers are essential for operation. The solution enhances precision in event-driven systems by narrowing the event criteria to specific times or days, reducing unnecessary activations and ensuring tasks are performed at the intended intervals.
7. The method as defined in claim 1 , wherein the transaction data for each said transaction is received from at least one account issuer for the corresponding said accountholder.
A system and method for processing financial transactions involves receiving transaction data for multiple transactions, where each transaction is associated with an accountholder. The transaction data for each transaction is obtained from at least one account issuer corresponding to the accountholder. The system processes this transaction data to generate a consolidated view of the accountholder's financial activities across multiple accounts. This consolidated view may include transaction details, account balances, and other relevant financial information. The system may also analyze the transaction data to detect fraud, identify spending patterns, or provide personalized financial recommendations. The method ensures that transaction data is securely transmitted and processed, maintaining the privacy and integrity of the financial information. The system may be used by financial institutions, payment processors, or other entities involved in financial transactions to provide a comprehensive overview of an accountholder's financial activities. The method improves efficiency by centralizing transaction data from multiple sources, reducing the need for manual data entry and minimizing errors. Additionally, the system may support real-time or near-real-time processing of transaction data, allowing for timely updates and alerts to accountholders. The method may also integrate with other financial services, such as budgeting tools or investment platforms, to provide a seamless financial management experience.
8. A system comprising: at least one processor; memory storing instructions executable at the at least one processor to cause the system to: receive transaction data reflective of completed transactions; and for each said completed transaction: process the received transaction data to identify at least one accountholder attribute; identify: a merchant; at least one accountholder; and an anticipated transaction between the merchant and the at least one accountholder; generate, using a neural network of an artificial intelligence engine, a recommended incentive for the identified at least one accountholder based on the at least one accountholder attribute, wherein: the recommended incentive defines a benefit to be provided by the identified merchant to the identified at least one accountholder upon the occurrence of the anticipated transaction; and the benefit is that the merchant of the anticipated transaction has agreed to make a donation to an entity designated by the identified at least one accountholder upon the occurrence of the anticipated transaction at: a predetermined time of day; and a predetermined geographic location; and for the identified at least one accountholder, electronically transmitting to a logical address corresponding to the identified at least one accountholder an alert of the benefit.
The system operates in the domain of financial transaction processing and incentive-based marketing, addressing the challenge of increasing customer engagement and loyalty by leveraging transaction data to offer personalized incentives. The system processes completed transaction data to extract accountholder attributes, such as spending habits or preferences, and identifies merchants, accountholders, and anticipated future transactions between them. Using a neural network within an artificial intelligence engine, the system generates a recommended incentive tailored to the accountholder based on their attributes. The incentive involves a merchant agreeing to make a donation to an entity designated by the accountholder upon the occurrence of the anticipated transaction, with the donation occurring at a predetermined time and location. The system then transmits an electronic alert to the accountholder, notifying them of the benefit. This approach aims to drive transactions by aligning merchant offers with accountholder preferences, particularly through charitable contributions, thereby enhancing customer satisfaction and loyalty. The system automates the identification of transaction patterns, incentive generation, and communication, streamlining the process of personalized marketing.
9. The system as defined in claim 8 , wherein the instructions are further executable at the at least one processor to cause the system to generate an alert to notify the identified merchant of an identified event or trend.
The invention relates to a system for monitoring and analyzing merchant transactions to detect events or trends that may require attention. The system processes transaction data from multiple merchants to identify patterns, anomalies, or other significant occurrences. It includes at least one processor and memory storing instructions that, when executed, enable the system to analyze transaction data to detect events or trends. The system can identify specific events, such as fraudulent transactions or unusual spending patterns, or broader trends, such as shifts in customer behavior or seasonal fluctuations. Once an event or trend is detected, the system generates an alert to notify the relevant merchant. This alert allows the merchant to take appropriate action, such as investigating suspicious activity or adjusting business strategies. The system may also include additional features, such as generating reports or visualizations of the detected events or trends to provide merchants with detailed insights. The goal is to enhance merchant awareness and decision-making by proactively identifying and communicating significant transaction-related occurrences.
10. The method as defined in claim 9 , wherein the identified event is selected from the group consisting of: a particular time of day; and a particular day of week.
A system and method for event-based data processing involves detecting and responding to specific events to trigger data operations. The system monitors for predefined events, such as a particular time of day or a specific day of the week, and executes corresponding actions when these events occur. These actions may include data retrieval, analysis, storage, or transmission, depending on the application. The method ensures that data processing tasks are performed in response to temporal conditions, improving efficiency and automation in systems that rely on scheduled or periodic operations. The system may be integrated into various applications, such as scheduling systems, data logging, or automated reporting, where time-based triggers are essential for functionality. The method enhances reliability by ensuring that data operations are performed at the correct intervals, reducing manual intervention and potential errors. The system may also include additional event types beyond time-based triggers, allowing for flexible and scalable event-driven processing.
11. The system as defined in claim 8 , wherein the anticipated transaction is identified based on the identified at least one accountholder attribute.
A system for identifying anticipated transactions in a financial context analyzes accountholder attributes to predict future transactions. The system processes transaction data and accountholder information to detect patterns or characteristics that correlate with specific transaction types. By evaluating attributes such as transaction history, spending habits, demographic data, or behavioral patterns, the system determines the likelihood of certain transactions occurring. This predictive capability enables proactive actions, such as fraud detection, personalized recommendations, or automated approvals. The system may also integrate with external data sources to enhance accuracy. The identified attributes are used to refine transaction predictions, ensuring relevance and reducing false positives. This approach improves decision-making in financial services by leveraging data-driven insights to anticipate and manage transactions efficiently.
12. The system as defined in claim 11 , wherein the at least one accountholder attribute is based on criteria selected from the group consisting of: a “Bank Identification Number” (BIN) range; the transaction and the merchant; demographics of the accountholder; and preferences of the identified at least one accountholder, wherein the at least one accountholder is identified based on the preferences.
This invention relates to a financial transaction system that customizes transaction processing based on accountholder attributes. The system addresses the problem of generic transaction handling, which fails to account for individual accountholder preferences, demographics, or transaction-specific factors, leading to inefficiencies and suboptimal user experiences. The system identifies accountholders using criteria such as Bank Identification Number (BIN) ranges, transaction details, merchant information, accountholder demographics, or user preferences. Once identified, the system applies these attributes to tailor transaction processing. For example, transactions may be routed differently, approved or declined based on specific rules, or modified to align with user preferences. The system dynamically adjusts processing logic based on real-time data, ensuring transactions are handled in a way that reflects the accountholder’s profile or situational context. By incorporating these attributes, the system enhances security, personalization, and efficiency in transaction handling. For instance, a transaction involving a high-risk merchant may be flagged for additional verification if the accountholder’s demographics indicate a higher fraud risk. Alternatively, a frequent traveler’s transactions abroad may be automatically approved without additional scrutiny. The system ensures that transaction decisions are context-aware, reducing false positives in fraud detection and improving user satisfaction.
13. The system as defined in claim 11 , wherein: the at least one accountholder attribute is based on a transaction history of the identified at least one accountholder; and the transaction history identifies purchases of goods and services, and merchants the goods and services were purchased from.
A financial transaction analysis system monitors and evaluates accountholder behavior by analyzing transaction histories to identify patterns in purchases of goods and services. The system tracks not only the transactions themselves but also the merchants involved, allowing for detailed profiling of accountholder attributes. By examining spending habits, frequency of purchases, and merchant preferences, the system generates insights into accountholder preferences, financial behavior, and potential risks. This data can be used for fraud detection, personalized marketing, credit risk assessment, or targeted financial product recommendations. The system dynamically updates accountholder profiles based on ongoing transaction activity, ensuring real-time relevance. The analysis may include categorizing transactions by merchant type, purchase frequency, and spending trends to refine behavioral models. This approach enhances decision-making for financial institutions by providing a comprehensive view of accountholder interactions with merchants and their spending patterns. The system may also integrate external data sources to further enrich transaction history analysis, improving accuracy and predictive capabilities.
14. The method as defined in claim 8 , wherein the transaction data for each said transaction is received from at least one account issuer for the corresponding said accountholder.
A system and method for processing financial transactions involves securely receiving and validating transaction data from multiple account issuers. The method includes obtaining transaction data for each transaction, where the data is provided by the account issuer associated with the accountholder involved in the transaction. This data may include transaction details such as amount, timestamp, and participant information. The system then processes this data to verify its authenticity and accuracy, ensuring that the transaction is legitimate and authorized. The method may also involve aggregating transaction data from multiple issuers to provide a comprehensive view of an accountholder's financial activity. This approach enhances security by directly sourcing transaction data from the issuer, reducing the risk of fraud or unauthorized access. The system may further include mechanisms to detect anomalies or discrepancies in the transaction data, alerting relevant parties to potential issues. By centralizing transaction data from multiple issuers, the method improves efficiency in financial processing and reporting, benefiting both accountholders and issuers. The system may also support real-time or near-real-time data updates to ensure timely and accurate financial tracking.
15. A non-transitory computer-readable medium or media storing computer instructions which when executed by at least one computer processor causes the at least one computer processor to perform a method comprising: receiving transaction data reflective of each of a plurality of completed transactions; and for each said transaction: processing the received transaction data to identify at least one accountholder attribute; identifying a merchant; identifying at least one accountholder; identifying an anticipated transaction between the merchant and the at least one accountholder; generating, using a neural network of an artificial intelligence engine, a recommended incentive for the identified at least one accountholder based on the at least one accountholder attribute, wherein: the recommended incentive defines a benefit to be provided by the identified merchant to the identified at least one accountholder upon the occurrence of the anticipated transaction; and the benefit is that the merchant of the anticipated transaction has agreed to make a donation to an entity designated by the identified at least one accountholder upon the occurrence of the anticipated transaction at: a predetermined time of day; and a predetermined geographic location; and for the identified at least one accountholder, electronically transmitting to a logical address corresponding to the identified at least one accountholder an alert of the benefit.
This invention relates to a system for generating and delivering personalized incentives to accountholders based on transaction data and artificial intelligence. The system processes transaction data from completed transactions to identify accountholder attributes, such as spending habits, preferences, or other relevant characteristics. It also identifies the merchant involved in the transaction and the accountholder. Using this information, the system predicts an anticipated future transaction between the merchant and the accountholder. A neural network within an artificial intelligence engine then generates a recommended incentive tailored to the accountholder based on their attributes. The incentive involves the merchant agreeing to make a donation to an entity designated by the accountholder upon the occurrence of the anticipated transaction. The donation is scheduled to occur at a predetermined time of day and geographic location. The system then electronically transmits an alert to the accountholder, notifying them of the benefit. This approach leverages transaction history and AI to create personalized, location- and time-specific incentives that encourage transactions while supporting charitable causes.
16. The non-transitory computer-readable medium or media storing computer instructions as defined in claim 15 , wherein the instructions are further executable at the at least one processor to cause the system to generate an alert to notify the identified merchant of an identified event or trend.
A system and method for monitoring and analyzing merchant transactions to detect events or trends. The system processes transaction data from multiple merchants to identify patterns, anomalies, or trends that may indicate fraud, operational issues, or business opportunities. The system includes a data processing module that collects and normalizes transaction data, an analysis module that applies machine learning or statistical techniques to detect events or trends, and an alerting module that generates notifications for merchants. The alerting module notifies merchants of detected events or trends, such as unusual transaction volumes, fraudulent activity, or shifts in customer behavior. The system may also provide recommendations or actions to address the identified issues. The alerting mechanism ensures merchants are promptly informed, allowing them to take corrective or preventive measures. The system may operate in real-time or batch processing modes, depending on the requirements. The technology is applicable to financial institutions, payment processors, and e-commerce platforms seeking to enhance transaction monitoring and merchant support.
17. The non-transitory computer-readable medium or media storing computer instructions as defined in claim 16 , wherein the identified event is selected from the group consisting of: a particular time of day; and a particular day of week.
A system and method for event-based data processing involves monitoring data streams to detect predefined events, such as specific times of day or days of the week. The system processes incoming data in real-time, comparing it against stored event criteria to identify matches. When an event is detected, the system triggers a predefined action, such as generating an alert, updating a database, or executing a secondary process. The event criteria can be configured to recognize recurring temporal patterns, allowing for automated responses to scheduled or periodic occurrences. The system may also filter or prioritize data based on event relevance, ensuring efficient resource utilization. This approach enables automated decision-making and workflow management in applications like scheduling, monitoring, or data analysis, where time-based triggers are essential. The system can be integrated into larger data processing frameworks, providing flexibility in event definition and action execution. The use of non-transitory computer-readable media ensures persistent storage and retrieval of event definitions and associated actions, supporting reliable and scalable event-driven operations.
18. The non-transitory computer-readable medium or media storing computer instructions as defined in claim 15 , wherein the anticipated transaction is identified based on the identified at least one accountholder attribute.
A system and method for identifying and processing anticipated financial transactions based on accountholder attributes. The technology addresses the problem of inefficient transaction processing and fraud detection by leveraging accountholder data to predict and validate transactions in real-time. The system analyzes stored transaction data and accountholder attributes, such as spending habits, account history, and demographic information, to identify patterns and predict future transactions. When a transaction is initiated, the system compares it against these predictions to determine if it matches expected behavior. If the transaction aligns with the anticipated patterns, it is processed normally. If discrepancies are detected, the system may flag the transaction for further review or apply additional security measures. The system also includes a machine learning component that continuously updates its predictive models based on new transaction data and user feedback, improving accuracy over time. This approach enhances transaction security, reduces false positives in fraud detection, and streamlines the approval process for legitimate transactions. The invention is particularly useful in banking, payment processing, and financial services, where accurate and efficient transaction handling is critical.
19. The non-transitory computer-readable medium or media storing computer instructions as defined in claim 18 , wherein the at least one accountholder attribute is based on criteria selected from the group consisting of: a “Bank Identification Number” (BIN) range; the transaction and the merchant; demographics of the accountholder; and preferences of the identified at least one accountholder, wherein the at least one accountholder is identified based on the preferences.
This invention relates to a system for processing financial transactions using a non-transitory computer-readable medium that stores instructions for identifying accountholders and applying transaction rules based on specific attributes. The system addresses the problem of efficiently managing and customizing transaction processing based on accountholder characteristics, ensuring secure and tailored financial operations. The computer-readable medium stores instructions that, when executed, identify at least one accountholder attribute from a predefined set of criteria. These criteria include a Bank Identification Number (BIN) range, transaction and merchant details, accountholder demographics, and accountholder preferences. The system uses these attributes to determine transaction rules, such as approval or denial, based on the identified accountholder. For example, transactions may be approved or restricted based on the BIN range, merchant type, or demographic data. Additionally, the system allows for transaction processing to be influenced by accountholder preferences, ensuring personalized financial management. The instructions further enable the system to analyze transaction data in real-time, applying the identified attributes to enforce security measures or optimize transaction flow. This approach enhances fraud detection, compliance, and user experience by dynamically adjusting transaction handling based on the accountholder’s profile. The system ensures flexibility and adaptability in financial transaction processing, catering to diverse accountholder needs and regulatory requirements.
20. The non-transitory computer-readable medium or media storing computer instructions as defined in claim 15 , wherein: the at least one accountholder attribute is based on a transaction history of the identified at least one accountholder; and the transaction history identifies purchases of goods and services, and merchants the goods and services were purchased from.
This invention relates to financial transaction analysis and personalized account management. The problem addressed is the need for more accurate and context-aware account management by leveraging transaction history to determine accountholder attributes. The system analyzes transaction data to identify patterns, preferences, and behaviors of accountholders, such as frequently purchased goods and services and preferred merchants. This information is used to customize account features, recommendations, or security measures. The transaction history includes details like purchase amounts, dates, and merchant information, enabling the system to derive meaningful insights about the accountholder. By correlating transaction data with accountholder attributes, the system enhances personalization, fraud detection, and targeted financial services. The approach improves decision-making for both accountholders and financial institutions by providing a data-driven understanding of spending habits and merchant interactions. This method ensures that account management is tailored to individual needs, improving user experience and security.
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October 17, 2020
February 15, 2022
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